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Article
Encrypted Image Retrieval System Based on Features Analysis

Author: Methaq T. Gaata
Journal: Al-Mustansiriyah Journal of Science مجلة علوم المستنصرية ISSN: 1814635X Year: 2017 Volume: 28 Issue: 3 Pages: 166-173
Publisher: Al-Mustansyriah University الجامعة المستنصرية

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Abstract

Content-based search provides an important tool for users to consume the ever-growing digital media repositories. However, since communication between digital products takes place in a public network, the necessity of security for digital images becomes vital. Hence, the design of secure content-based image retrieval system is becoming an increasingly demanding task as never before. In this paper, the secure CBIR with additional improvement for the image retrieval has been presented. The proposed system consists of six phases briefly described as follows: first, feature extraction phase, which produces the low-level quantitative description of the image (color and texture) that used in calculation of similarity score and image indexing. Second, indexing for search process phase, hash table and bloom filter were employed for classification. Third, feature encryption phase, where content protection is performed using a method developed by us (including Chaotic Logistic Map). Fourth, image encryption phase, the chaos and stream cipher systems were applied as an image encryption system in order to achieve image security. Fifth, the retrieval phase, which provides a group of images replying the query based on the similarity score between images, calculated using the extracted features from each image. Finally, Relevance feedback phase, a technique that attempts to capture the user’s needs through iterative feedback. Although the system proved its efficiency in search performance (with 88% of average precision), security strength, and computational complexity, it does not mean the optimal system is designed, since some weakness points still can be found that are suggested to be improved as a future work.


Article
Content-based Image Retrieval using Texture and Color Features

Authors: Abbas Hanon AL-Asadi --- Ali Basim AL-Khafaji
Journal: JOURNAL OF THI-QAR SCIENCE مجلة علوم ذي قار ISSN: 19918690 Year: 2013 Volume: 3 Issue: 4 Pages: 142-149
Publisher: Thi-Qar University جامعة ذي قار

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Abstract

The emergence of multimedia technology and the rapidly expanding image collections on the Internet have attracted significant research efforts in providing tools for effective retrieval and management of visual data. Content-based image retrieval has been an active area of research over last decade. In this paper, a content-based image retrieval system is presented. It supports querying by example to retrieve images from the images database according to their texture and color features. For feature extractions, Gray-Level Co-occurrence Matrix (GLCM) and color histogram of HSV have been used. The results appeared quite satisfactory.

أدى ظهور تكنولوجيا الوسائط المتعددة والتوسع السريع لمجاميع الصور على الانترنيت جهود بحثية مهمة في توفير الأدوات اللازمة للاسترجاع الفعال وإدارة البيانات المرئية . أن استرجاع الصور بالاعتماد على المحتويات يعتبر من مجالات البحث العلمي النشطة خلال السنوات الأخيرة. في هذا البحث , تم عرض نظام استرجاع صورة يعتمد على المحتويات يدعم الاستعلام عن طريق صورة وذلك لغرض استرجاع صور من قاعدة بيانات صورية بالاعتماد على صفاتها النسيجية (Texture) واللونية (Color Histogram). في هذا البحث , نستخدم مصفوفة الظهور المتلازم للألوان الرمادية لاستخراج صفات النسيج ونستخدم أيضا المدرج الإحصائي للنموذج اللوني كصفة لونية . النتائج كانت مرضية جدا.


Article
A Proposal of an Efficient Feature Extracting Method for Content-Based Image Retrieval

Authors: Batool Hussein Farhan --- Israa Tahseen Ali
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2016 Volume: 34 Issue: 6 Part (B) Scientific Pages: 777-785
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Searching a required image from the World Wide Web (WWW) is very difficult because the WWW contains a huge number of images. To solve such a problem, an efficient system is needed to retrieve images that are required by the user. The content-based image retrieval (CBIR) system has been used to solve this problem. In this paper, a new combination of three techniques is used for visual features extracting. Color histogram was used to extract color feature from the image. Multi wavelet transform was chosen to represent the information of the texture and the edge histogram was used to represent the shape feature. Object scaling and translation in an image can be got robustly by the combination of these techniques. Furthermore, to speed up retrieval and similarity computation of the proposed system, the data set images are clustered using k-mean clustering algorithm according to the weighted feature vectors. The system evaluation experimentally carried out on800Wang color image dataset, and showed that proposed system performed significantly better and faster than other existing systems by using the proposed features.


Article
A Novel Algorithm for Diagnosis of Thin Basement Membrane Nephropathy
خوارزمية تشخيص مرض الغشاء الكلوي الوراثي

Author: Alyaa Muhsen Manaty علياء محسن منات
Journal: Journal of Engineering and Sustainable Development مجلة الهندسة والتنمية المستدامة ISSN: 25200917 Year: 2013 Volume: 17 Issue: 3 Pages: 186-199
Publisher: Al-Mustansyriah University الجامعة المستنصرية

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Abstract

In this paper we have made an algorithm to diagnose the thin basement membrane nephropathy. The idea of our algorithm is based on content based image retrieval and Hough transform. The diagnosis of this disease is depending on calculating the membrane thickness to know whether it is normal or abnormal. The traditional way for calculating the thickness is by manually enlarging the pictures for more than 5 thousand times before calculating the thickness, so we suggest an automatic algorithm to detect the membrane in the pictures then calculates the thickness. Firstly, a database of the membrane shapes will be build by dividing the original image of size 512512 pixel into sub images of size7070 pixel, the sub image that contain membrane will be considered, other parts will be ignored. Then, the sub image that contain the membrane will be enhanced and converted into binary image to detect the edges, Hough transform and line detect method are used to detect the surface of the membrane by drawing lines on the surface of the membrane, by applying orthogonal line on two lines that lies on the corresponding membrane surface, we then calculated the distance between two lines by using Euclidian distance. Compared with the manual procedures, our algorithm proves easy to use and can work round the clock.

اقترحنا في هذا البحث خوارزمية لتشخيص مرض وراثي يصيب الكلية وهذا المرض يصيب الغشاء الخارجي المحيط بكل خلية في الكلية حيث يكون السمك للغشاء مقياس للإصابة بهذا المرض اولاَ . فكرة الخوارزمية مستوحاة من استرجاع محتوى الصورة وتحويلات هوغ. تشخيص هذا المرض يعتمد على حساب سمك الغشاء لمعرفة ما إذا كان السمك طبيعي ام غير طبيعي. حيث كانت الطريقة التقليدية لحساب سمك الخلية يدويا عن طريق تكبير الصور لأكثر من 5 الاف مرة ومن ثم استخدام القياس اليدوي لحساب السمك ، لذلك اقترحنا خوارزمية تقوم اولا بالكشف عن الغشاء فقط وترك باقي اجزاء الخلية ومن ثم يحسب سمك الغشاء. والخوارزمية تقوم بالتالي: أولاَ: سيتم بناء قاعدة بيانات من الأشكال الخاصة للغشاء عن طريق تقسم حجم الصورة الأصلية من 512 512 بكسل إلى اجزاء من الصورة بحجم 7070 بكسل ، الصور الفرعية التي تحتوي على الغشاء سوف تؤخذ بنظر الاعتبار ، اما باقي الصور او الاجزاء الاخرى سيتم تجاهلها. ثم، نقوم بتحسين الصور الفرعية التي تحتوي على الغشاء وتحويلها إلى صورة الثنائية للكشف عن الحواف، حيث يستخدم تحويلات هوغ وطريقة كشف الخط للكشف عن سطح الغشاء وذلك عن طريق رسم خطوط على سطح الغشاء، حيث يتم رسم خط متعامد على خطين يتم رسمهما افقيا والذين يقعان على سطح غشاء بصورة متقابلة (خط في اعلى الغشاء وخط اسفل الغشاء )، ومن ثم نقوم بحساب المسافة بين خطين باستخدام نظرية اقليدس حيث كانت النتائج ممتازة بالمقارنه مع الطريقة اليدوية، الخوارزمية اثبتت سهولة في الاستخدام ويمكن أن تعمل على مدار الساعة.


Article
Face Recognition and Retrieval based on Wavelet Transform Using Association Rules in Android Operating System
التعرف على الوجه واسترجاعها على أساس تحويل المويجات باستخدام قوانين الرابطة في نظام التشغيل أندرويد

Authors: Abdul-Wahab Sami Ibrahim --- Raniah Ali Mustafa
Journal: Iraqi Journal of Information Technology المجلة العراقية لتكنولوجيا المعلومات ISSN: 19948638/26640600 Year: 2016 Volume: 7 Issue: 2 اللغة الانكليزية Pages: 98-117
Publisher: iraqi association of information الجمعية العراقية لتكنولوجيا المعلومات

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Abstract

In this paper, we propose face detection approach was successfully implemented on Android Operating System version (4.3) which involved programming in Java language version 6 and face recognition system successfully implemented in programming language visual basic 6.0. The main idea of the proposed system depends on the fact that any face image person has multi unique features. These features are different from one face image to another. Our proposed algorithm depends on wavelet transform to extract features from the face image person to extract association rules between these features to recognition face images person and retrieval. And then each face image is stored with its association rules in the association rules database to be used in face image recognition and retrieval systems. From experiments and test results it is noted that behavior of proposed face detection approach leads to higher detection performance results, face recognition and retrieval approach leads to higher performance results for most classes. The system was tested over a database collected from 30 volunteers, where 15 images for each person were collected under different lighting conditions, varied in expression, orientations, illumination, skin color, background, ages, and faces shapes (the mouth and eyes are open or closed, with or without glasses, male and female... etc.). The achieved training rate was 100% and recognition rate (72%) and the average of precision (70.5%) were achieved.

في هذا البحث , أقترحنا طريقة الكشف عن الوجه نفذت بنجاح على نظام التشغيل الأندرويد الأصدار (4.3) التي تشمل البرمجة بلغة الجافا الأصدار 6 ونظام التعرف على الوجه نفذت بنجاح في لغة البرمجة visual Basic 6.0. الفكرة الرئيسية لنظام المقترح تعتمد على أن أي صورة لها مميزات فريدة متعددة. هذه الميزات تختلف من صورة وجه إلى أخرى. الخوارزمية المقترحة تعتمد على تحويل المويجات لأستخراج الخصائص من صورة وجه الشخص لأستخراج العلاقات الترابطية بين هذه الخصائص لتمييز صورة وجه الشخص وأسترجاعها.ثم تخزين كل صورة مع قواعدها الترابطية في قاعدة بيانات القواعد الترابطية لأستخدامها في نظام تمييز الوجه وأسترجاعها. من نتائج الاختبار لاحظنا أن سلوك النهج الكشف عن الوجه المقترح يؤدي الى نتائج أداء عالية, التعرف على الوجه وطريقة أسترجاعها يؤدي الى نتائج أداء عالية لمعظم فئات صور الوجه. تم اختبار النظام على قاعدة بيانات تم جمعها من 30 متطوعا، حيث تم جمع 15 صورة لكل شخص جمعت في ظل ظروف إضاءة مختلفة, ومتنوعة في التعبير, وتوجاتها, والاضاءة, ولون البشرة, الخلفية, الأعمار وشكل الوجوه (الفم والعيون مفتوحة أو مغلقة, مع أو بدون نظارات, ذكوراً وإناثاً......الخ). حققت معدل التدريب (%100) وحققت معدل تمييز ( 72% ) ومتوسط الدقة (70.5%).


Article
A Content-Based Image Retrieval Method By Exploiting Cluster Shapes

Authors: Hanan Al-Jubouri --- Hongbo Du
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2018 Volume: 14 Issue: 2 Pages: 90-102
Publisher: Basrah University جامعة البصرة

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Abstract

Content-Based Image Retrieval (CBIR) is an automatic process of retrieving images that are the most similar to a query image based on their visual content such as colour and texture features. However, CBIR faces the technical challenge known as the semantic gap between high level conceptual meaning and the low-level image based features. This paper presents a new method that addresses the semantic gap issue by exploiting cluster shapes. The method first extracts local colours and textures using Discrete Cosine Transform (DCT) coefficients. The Expectation-Maximization Gaussian Mixture Model (EM/GMM) clustering algorithm is then applied to the local feature vectors to obtain clusters of various shapes. To compare dissimilarity between two images, the method uses a dissimilarity measure based on the principle of Kullback-Leibler divergence to compare pair-wise dissimilarity of cluster shapes. The paper further investigates two respective scenarios when the number of clusters is fixed and adaptively determined according to cluster quality. Experiments are conducted on publicly available WANG and Caltech6 databases. The results demonstrate that the proposed retrieval mechanism based on cluster shapes increases the image discrimination, and when the number of clusters is fixed to a large number, the precision of image retrieval is better than that when the relatively small number of clusters is adaptively determined.


Article
CONTENT-BASED IMAGE RETRIEVAL: SURVEY

Author: Hanan Ahmed Al-Jubouri
Journal: Journal of Engineering and Sustainable Development مجلة الهندسة والتنمية المستدامة ISSN: 25200917 Year: 2019 Volume: 23 Issue: 3 Pages: 42-63
Publisher: Al-Mustansyriah University الجامعة المستنصرية

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Abstract

Extensive use of digital photographic devices has resulted in large volumes of digital images being acquired and stored in databases. Whether it is for scientific research, medical or social networking, there is a growing demand for effective retrieval of digital images based on their visual content (e.g. colour and texture). Content-Based Image Retrieval systems are developed to meet this demand. However, searching for similar and relevant images from large-scale databases still poses a challenge for Content-Based Image Retrieval systems due to the gap between high-level meaning and low-level visual features. This paper reviews different Content-Based Image Retrieval approaches such as Clustering, Region-of-Interest, Bag-of-Visual-Words, Relevance Feedback, Browsing, and indexing that have been developed to reduce such “Semantic gap” issue. So, the interested researchers can interest to determine which method is benefit to his work.

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